1. Technical Field
This disclosure relates generally to image adjustment and, more specifically, to automatic image adjustments.
2. Description of the Related Art
Adjusting photographs is a tedious process that requires skill and time. The difference between a picture that comes straight from the camera and a carefully adjusted one can be dramatic just by balancing the tones and revealing the interplay of light. To adjust a photograph, photographers need to consider the image content and the tonal challenges it presents. Even adjusting contrast and tonal balance is challenging because it must take into account the photo subject and lighting conditions.
Decision factors in photograph adjusting are often subjective and cannot be directly embedded into algorithmic procedures. Some photo editing packages offer automatic adjustment, however, many offer a simple heuristic that fails to address more complex adjustments that depend upon scene characteristics such as low versus high key, scenes with back-lighting, or other difficult lighting situations. Other packages may apply simple rules, such as fixing the black and white points of the image to the darkest and brightest pixels. Although this may work in simple cases, these approaches fail in more complex examples, in which a photographer would apply more sophisticated modifications. Because of the complexities inherent in photograph adjusting, rule-based automatic techniques for adjusting photographs often fail.
Moreover, different image processing tools may use different image processing pipelines. For example, one tool may apply image processing operations in gamma-corrected RGB color space while another may perform operations in LAB or CMYK color space. The effects of image processing operations performed in different color spaces may differ widely. Oftentimes, no close-form mapping exists between such operations. Further, image processing pipelines often differ not only in color spaces but in the details of image processing operations.